Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock from around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology, quickly and accurately. We apply problem-solving skills to identify workflow efficiencies, implement technology solutions to enhance our systems, products, and processes, and provide support to our clients.

Our Team

The Bloomberg Data AI group brings cutting-edge AI technologies into Bloomberg’s Data organization, supplying deep domain expertise to the development of AI-powered products. One of our core areas focuses on Dialogue Labeling and Annotation Management, supporting Natural Language Processing (NLP) enrichments across multiple communication platforms. These enrichments are essential for structuring unstructured client communications and fueling intelligent downstream search, classification, summarization, and insight generation.

Our team builds and runs scalable annotation frameworks, driving quality training and evaluation datasets. We partner closely with Product and Engineering to elevate the performance of Machine Learning (ML) models, enrichments, and features delivered to clients. Looking forward, our roadmap includes expansion into communication-based search insights and further enhancements of ML enrichments.

What’s The Role

As a Data Product Owner, you are a true hybrid professional – a link between deep financial domain expertise and innovative technology. You will play a pivotal role in solving sophisticated data challenges in finance by ensuring our data collection, documentation, and tooling adhere to MDLC (Machine Learning Development Lifecycle) protocols.

This role requires a strategic approach around ML training data design, a solid understanding of data modeling and schema architecture, and the ability to align data strategies with product objectives. You will also help craft data pipelines and annotation schemas that support search relevance modeling, query understanding, and text summarization, enabling fast, relevant, and credible information delivery from communication streams. You'll be encouraged to guide the data design that supports extracting intent, identifying salient content, and generating concise responses or insights that drive decision-making for Bloomberg clients. You may also be responsible for providing support for our NLP solutions in other domains involving sophisticated financial instruments.

We’ll Trust You ToOwn the end-to-end Annotation Lifecycle, from schema development to annotation execution, with an eye toward ML performance and product utility.Bridge the gap between finance and AI/ML by mastering domain-specific concepts that elevate communications experiences.Design and run annotation programs for search and summarization use cases, including training data for relevance ranking, query-document matching, and text abstraction.Develop scalable strategies for data labeling and dialogue annotation, tailored for NLP enrichments across communication products.Build and evolve schematic structures and data models that serve as the foundation for annotation quality and reuse.Define metadata structures and enrichment tags that help interpret communication context, intent, and relevance to user queries.Collaborate with ML engineers and product partners to align annotation efforts with model requirements and product goals.Drive quality and consistency across annotation processes by developing clear guidelines, validation metrics, and governance frameworks.Leverage insights and analytics to iterate on annotation strategies and measure downstream model and product impact.Lead efforts to improve annotation efficiency, coverage, and enrichment scope by identifying automation and optimization opportunities.Stay ahead of trends in search technologies, summarization architectures, and standards for building reliable training datasets in these domains.Serve as a domain authority in data structuring, labeling, and ML data design within communications-focused NLP use cases.You’ll Need to Have4+ years of experience working in AI/ML data roles, ideally focused on NLP, communications, or information extraction.Shown experience with annotation programs, dialogue labeling, or large-scale training/evaluation dataset development.Solid grasp of data modeling, schema design, and protocols for structuring unstructured data.Familiarity with search infrastructure and summarization models, and how data influences relevance ranking and response generation.Ability to design, scale, and govern data pipelines that support high-impact ML model training and evaluation.Comfort engaging with ML practitioners to co-design data schemas and evaluate performance trade-offs.Excellent project management skills and the ability to run opposing priorities across multiple partners.We’d Love to SeeKnowledge of Python, SQL, and common ML/NLP tooling.Experience working with annotation tools or platforms (e.g., Prodigy, Labelbox, Snorkel, etc.).Background in information retrieval, semantic search, or abstractive summarization.Familiarity with model lifecycle practices (training, fine-tuning, evaluation).Experience with generative AI systems and timely evaluation workflows.Certification in data governance (e.g., DAMA CDMP, DCAM). Salary Range = 110000 - 190000 USD Annually + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.


We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.